Efficient encoder for low-density-parity-check codes

Abstract

Encoder circuitry for applying a low-density parity check (LDPC) code to information words is disclosed. The encoder circuitry takes advantage of a macro matrix arrangement of the LDPC parity check matrix in which a left-hand portion of the parity check matrix is arranged as an identity macro matrix, each entry of the macro matrix corresponding to a permutation matrix having zero or more circularly shifted diagonals. The encoder circuitry includes a cyclic multiply unit, which includes a circular shift unit for shifting a portion of the information word according to shift values stored in a shift value memory for the matrix entry, and a bitwise exclusive-OR function for combining the shifted entry with accumulated previous values for that matrix entry. Circuitry for solving parity bits for row rank deficient portions of the parity check matrix is also included in the encoder circuitry.

Description

CROSS-REFERENCE TO RELATED APPLICATIONS[0001]This application claims priority, under 35 U.S.C. §119(e), of Provisional Application No. 60 / 442,945, filed Jan. 27, 2003.STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT[0002]Not applicable.BACKGROUND OF THE INVENTION[0003]This invention is in the field of data communications, and is more specifically directed to redundant coding for error detection and correction in such communications.[0004]High-speed data communications, for example in providing high-speed Internet access, is now a widespread utility for many businesses, schools, and homes. In its current stage of development, this access is provided according to an array of technologies. Data communications are carried out over existing telephone lines, with relatively slow data rates provided by voice band modems (e.g., according to the current v.92 communications standards), and higher data rates provided by Digital Subscriber Line (DSL) technology. Another current t...

AI Technical Summary

Benefits of technology

[0014]It is a further object of this invention to provide such an architecture that provides flexibility relative to the specific LDPC codes being applied.

[0016]The present invention may be implemented into circuitry for applying LDPC encoding to data words for transmission over a communications facility. The encoder includes a memory for storing precalculated values of the parity matrix corresponding to the LDPC code; this precalculation is based on matrix operations that factor the parity matrix into a block matrix having a substantial portion in the form of an identity block matrix, with remaining block entries having reasonably small values. The known information bits of the data word to be encoded are multiplied by matrix entries to derive a set of right-hand side values. The encoder then includes a circular multiplier architecture, by way of which the parity bits are solved by a series of shifts and bitwise exclusive-OR operations, and the results accumulated. This encoder eliminates the need for storage of large inverse matrices, greatly improving the efficiency of the encoder and reducing its cost of implementation.

Problems solved by technology

A problem that is common to all data communications technologies is the corruption of data by noise.

In short, the likelihood of error in data communications must be considered in developing a communications technology.

Of course, this simple redundant approach does not necessarily correct every error, but greatly reduces the payload data rate.

In this example, a predictable likelihood remains that two of three bits are in error, resulting in an erroneous majority vote despite the useful data rate having been reduced to one-third.

But modern data words to be encoded are on the order of 1 kbits and larger, rendering lookup tables prohibitively large.

However, the computational efficiency in this and other conventional LDPC encoding techniques does not necessarily translate into an efficient encoder hardware architecture.

Specifically, these and other conventional encoder architectures are inefficient because the typically involve the storing of inverse matrices, by way of which the parity check equation (1) or a corollary is solved in the encoding operation.

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